07Why is the dot product the similarity score in attention and embeddings, and when should you normalize to cosine?▼mediumCohereOpenAIAnthropic1 repliesunlockedThe same operation scores attention and ranks your RAG results. Knowing exactly what the dot product measures, and when its magnitude term quietly breaks your retrieval, is what separates a working pipeline from a mysteriously bad one.Open full answer →
71Compute the dot product of two sparse vectors.▼mediumMetaGoogle1 replies◆ premiumThe whole question is the representation: store only the nonzeros as index→value, then either two-pointer over sorted indices or hash-join. The follow-up that decides the design is what happens when one vector is dense.Open full answer →
